The present invention is relates to machine vision systems for relative positioning of a component and a substrate for accurate semi-automatic placement of the component at a selected location on the substrate. While the specific examples discussed herein relate largely to the electronics assembly industry, the components placed may be electronic, electro-optic, electro-mechanical, optical, mechanical, micro-electronic machine (MEMS) devices, biological material, and the like, and may be of any size.
Robotic assembly equipment is well known in the art. Such equipment includes, for example, pick and place (or placement) machines. A placement machine is a robotic instrument for picking up electronic and similar parts from component feeders and placing them at their assigned locations on a printed circuit board (PCB). Once all parts are placed, the PCB is placed in a reflow oven and solder paste disposed on the PCB melts or xe2x80x9creflowsxe2x80x9d forming permanent electrical connections between conductive pads on the PCB and electrical contacts, leads or xe2x80x9cpinsxe2x80x9d on the electrical components.
Occasionally there are problems with the permanent electrical connections. For example, two pads of the PCB may become inadvertently bridged by solder, forming a short; the component may be mis-located; the component may prove faulty; and the like. In these situations, it is often economically desirable to salvage the partially assembled PCB rather than to scrap it. In order to salvage the PCB, one must remove the faulty component, re-prepare the PCB surface, and place and solder a new component (or a cleaned component) in the correct position on the PCB. This process is termed xe2x80x9creworkxe2x80x9d. Reworking thus involves reflowing the solder of an identified target component (and not that of the entire PCB), removing the faulty component; cleaning and refluxing the PCB in the location where the component is to be mounted, reinstalling the component and reflowing the solder for the component.
In the past, most known rework systems operate almost entirely manually, i.e., a skilled operator, using an optical magnification system which views both the PCB top surface and the component bottom surface, manually aligns the PCB and the component for placement. Placement systems, on the other hand, typically employ machine vision systems to automate this process. However, most known systems utilize a pair of imagers. One imager views the top surface of the PCB to obtain PCB alignment information by imaging known reference points on the PCB (known in the art as xe2x80x9cfiducialsxe2x80x9d) and/or by imaging contact pads on the PCB, another imager views the component, its bottom and/or its sides, to determine component alignment information. Since skilled operators are relatively expensive to train and employ, it would be desirable to employ a semi-automatic machine vision solution to assist an operator in performing placement and rework functions placement and rework equipment.
A semiautomatic method for digital feature separation uses a trained sample selected by an operator using a software xe2x80x9ceye dropperxe2x80x9d tool or a similar region-of-interest tool to sample features of interest on a stored digital image of, for example, an electronic component such as pads, bumps or leads of the component. Pixels from the sampled features are analyzed and plotted based on their color hue and saturation values or gray scale intensity values. The range of such values is chosen by a user. A second digital image is then compared to the sampled feature data gathered by the xe2x80x9ceye dropperxe2x80x9d tool. If the color and intensity values of the pixels from the second digital image fall within a user defined acceptable absolute value range, then the locations and values of those pixels in the image are saved. Background or surrounding elements in the second digital image which do not fall within the acceptable value range are deleted and replaced with a code that makes these background or surrounding element locations appear as a graphic transparency. This process leaves only the features of interest in their original locations saved in the graphics memory surrounded by pixels that have been made video transparent. The resulting saved image which contains only the selected features is then laid over a live image such as that of a target substrate with corresponding features of interest. The operator then manually aligns the saved features from the component image over the corresponding features of the live image of the substrate to achieve component to substrate registration.